Neuro-Fuzzy Networks: Transparent Rule-Based Decision-Making

Abstract

Neuro-fuzzy networks are a transparent function approximation technique that embodies human-readable knowledge while retaining the performance of conventional neural architectures. Their transparency may facilitate human-in-the-loop eXplainable AI and knowledge transfer. Still, despite these advantages, there remains no universally agreed upon systematic design of said systems as their construction is often application-dependent. Here, we showcase how my research has evolved over time, and how it may be applicable to Western Kentucky University.

John Wesley Hostetter

Computer Science Ph.D. Student

My research interests include fuzzy logic, artificial intelligence, and machine learning.